The highly buffered Arabidopsis immune signaling network conceals the functions of its components

Rachel A. Hillmer, Kenichi Tsuda, Ghanasyam Rallapalli, Shuta Asai, William Truman, Matthew D. Papke, Hitoshi Sakakibara, Jonathan D.G. Jones, Chad L Myers, Fumiaki Katagiri

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

Plant immunity protects plants from numerous potentially pathogenic microbes. The biological network that controls plant inducible immunity must function effectively even when network components are targeted and disabled by pathogen effectors. Network buffering could confer this resilience by allowing different parts of the network to compensate for loss of one another’s functions. Networks rich in buffering rely on interactions within the network, but these mechanisms are difficult to study by simple genetic means. Through a network reconstitution strategy, in which we disassemble and stepwise reassemble the plant immune network that mediates Pattern-Triggered-Immunity, we have resolved systems-level regulatory mechanisms underlying the Arabidopsis transcriptome response to the immune stimulant flagellin-22 (flg22). These mechanisms show widespread evidence of interactions among major sub-networks—we call these sectors—in the flg22-responsive transcriptome. Many of these interactions result in network buffering. Resolved regulatory mechanisms show unexpected patterns for how the jasmonate (JA), ethylene (ET), phytoalexin-deficient 4 (PAD4), and salicylate (SA) signaling sectors control the transcriptional response to flg22. We demonstrate that many of the regulatory mechanisms we resolved are not detectable by the traditional genetic approach of single-gene null-mutant analysis. Similar to potential pathogenic perturbations, null-mutant effects on immune signaling can be buffered by the network.

Original languageEnglish (US)
Article numbere1006639
JournalPLoS genetics
Volume13
Issue number5
DOIs
StatePublished - May 2017

Bibliographical note

Funding Information:
This work was supported by grants MCB-0918908 and MCB-1518058 (FK and CLM) and IOS-1121425 and DBI-1146819 (FK) from the National Science Foundation, the Max Planck Society (KT), the Gatsby charitable foundation's support of The Sainsbury Laboratory (JDGJ), JSPS KAKENHI 15K18651 (SA), RIKEN Special Postdoctoral Research Fellowship (SA). RAH was partially supported by the University of Minnesota?s NIH/NIGMS training grant 2T32GM008347-21A1 and by Plant Biological Sciences Graduate Program Summer Fellowships from the University of Minnesota (RAH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank the University of Minnesota Genomics Center (UMGC), and especially Aaron Becker, for help in sequencing the GAIIx libraries that were sequenced in Minnesota. We thank the Minnesota Supercomputing Institute (MSI) for data storage. We thank Jane Glazebrook for useful suggestions and critical reading of the manuscript, Mikiko Kojima for assistance with hormone measurement, and Barbara Kunkel for leading us to the [38 ] reference.

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